An Analytic Model to Assist Academic Advisors
We detail how academic advisors at two land grand universities benefit from the identification of factors related to poor academic performance of first-year students. We used a multivariate statistical model and data from one institution to identify characteristics of students at-risk of earning low grade point averages. We showed through a second application of the statistical model that first-year dropout was directly related to grade point average.
Contributor Notes
Stephen L. DesJardins is Associate Professor; Center for the Study of Higher and Postsecondary Education, College of Education, at the University of Michigan. His research interests include strategic enrollment management issues, the study of student departure from college, policy analysis, and the economics of higher education. His work in these areas has been published in the Journal of Human Resources, Journal of Higher Education, Economics of Education Review, Research in Higher Education, Journal of College Student Retention, Journal of Student Financial Aid, and Higher Education: Handbook of Theory and Research.
Wang Jie is a doctoral candidate in the Educational Policy and Leadership Studies program in the College of Education, at the University of Iowa. Her research interests include student departure, management information, and student development.
